From Quantum Chemistry to Dynamics: Exploring Potential Inhibitors for Alongshan Virus RdRp Through Advanced Computational Techniques

Alongshan virus, abbreviated as ALSV, a newly identified tick-borne virus associated with human disease, belongs to the Flavivirus group. There is no drug or vaccine available for the emergent ALSV. Developing treatment from scratch through experimental methods is a time-consuming process. Modern drug discovery increasingly depends on computer-assisted design. Recent efforts in drug discovery utilize computational findings as cost-effective tools that enhance efficiency by providing extensive information about how compounds interact with their targets. This structured computational approach aims to develop unique, selective drugs to address this urgent health threat. This study aimed to identify an effective and specific RNA-dependent RNA polymerase (RdRp) Nonstructural 5 (NS5) inhibitor for ALSV, incorporating density functional theory (DFT) to evaluate compounds’ stability and reactivity, and performing docking studies to estimate binding affinities. Molecular dynamics (MDs) simulations analyzed the stability of protein–ligand complexes, and in silico ADMET analysis assessed the pharmacokinetic properties of all compounds. Three potential new compounds were identified through structure-based virtual screening of the active region of the RdRp NS5 protein using an FDA-approved ASINEX antiviral library. The screening identified compounds BDG_33958579, BDG_33901365 and BDG_33693468, with computed binding energy scores of −8.0 kcal/mol, −7.8 kcal/mol and −7.7 kcal/mol, respectively. Principal component analysis (PCA) studies and secondary structure analyses were performed to evaluate the stability of the complexes during the simulation period. Analysis of MMGB/PBSA of the simulation trajectories showed binding energy scores of −43.13 kcal/mol, −45.33 kcal/mol and −42.91 kcal/mol for BDG_33958579, BDG_33901365 and BDG_33693468, respectively, regardless of order. MM/PBSA binding energy values were −44.85 kcal/mol, −43.1 kcal/mol and −44.56 kcal/mol for the same compounds. Additionally, the studied compounds demonstrated favorable pharmacokinetic profiles and were identified as drug-like. The compounds have the potential to serve as novel drugs, and further experimental research could explore their anti-RdRp activity against ALSV.

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Publication Details

Journal
Journal of Computational Biophysics and Chemistry
Published
2025-08-15
DOI
https://doi.org/10.1142/s2737416525501133
Citations
1
Primary Topic
Plant Virus Research Studies
Type
article
Field-Weighted Citation Impact
1.75
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article

From Quantum Chemistry to Dynamics: Exploring Potential Inhibitors for Alongshan Virus RdRp Through Advanced Computational Techniques

Sumaira Nadeem, Sajjad Ahmad, Farhan Siddique, Kalsoom Khan et al.
1 citations
Journal of Computational Biophysics and Chemistry
Plant Virus Research Studies
1.75
article

From Quantum Chemistry to Dynamics: Exploring Potential Inhibitors for Alongshan Virus RdRp Through Advanced Computational Techniques

Sumaira Nadeem, Sajjad Ahmad, Farhan Siddique, Kalsoom Khan, Mohammad Abdullah Aljasir, Bushra Rehman, Saira
article en
1 citations

Abstract

Alongshan virus, abbreviated as ALSV, a newly identified tick-borne virus associated with human disease, belongs to the Flavivirus group. There is no drug or vaccine available for the emergent ALSV. Developing treatment from scratch through experimental methods is a time-consuming process. Modern drug discovery increasingly depends on computer-assisted design. Recent efforts in drug discovery utilize computational findings as cost-effective tools that enhance efficiency by providing extensive information about how compounds interact with their targets. This structured computational approach aims to develop unique, selective drugs to address this urgent health threat. This study aimed to identify an effective and specific RNA-dependent RNA polymerase (RdRp) Nonstructural 5 (NS5) inhibitor for ALSV, incorporating density functional theory (DFT) to evaluate compounds’ stability and reactivity, and performing docking studies to estimate binding affinities. Molecular dynamics (MDs) simulations analyzed the stability of protein–ligand complexes, and in silico ADMET analysis assessed the pharmacokinetic properties of all compounds. Three potential new compounds were identified through structure-based virtual screening of the active region of the RdRp NS5 protein using an FDA-approved ASINEX antiviral library. The screening identified compounds BDG_33958579, BDG_33901365 and BDG_33693468, with computed binding energy scores of −8.0 kcal/mol, −7.8 kcal/mol and −7.7 kcal/mol, respectively. Principal component analysis (PCA) studies and secondary structure analyses were performed to evaluate the stability of the complexes during the simulation period. Analysis of MMGB/PBSA of the simulation trajectories showed binding energy scores of −43.13 kcal/mol, −45.33 kcal/mol and −42.91 kcal/mol for BDG_33958579, BDG_33901365 and BDG_33693468, respectively, regardless of order. MM/PBSA binding energy values were −44.85 kcal/mol, −43.1 kcal/mol and −44.56 kcal/mol for the same compounds. Additionally, the studied compounds demonstrated favorable pharmacokinetic profiles and were identified as drug-like. The compounds have the potential to serve as novel drugs, and further experimental research could explore their anti-RdRp activity against ALSV.

Journal of Computational Biophysics and ChemistryVol. 25(11)
Bahauddin Zakariya University (PK), Qassim University (SA), Khyber Medical University (PK), Abasyn University (PK)
Openalex Percentile: Top 12%
Plant Virus Research Studies
1.75
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